code: def _maybe_create_instance() -> Optional[ModelInferenceAPI]:
      """This function tries to re-create the user `ModelInferenceAPI` if the environment associated with multi workers
      are present."""
      render_fn_name = os.getenv(
          "LIGHTNING_MODEL_INFERENCE_API_CLASS_NAME", None
      )
      render_fn_module_file = os.getenv(
          "LIGHTNING_MODEL_INFERENCE_API_FILE", None
      )
      if render_fn_name is None or render_fn_module_file is None:
          return None
      module = pydoc.importfile(render_fn_module_file)
      cls = getattr(module, render_fn_name)
      input = os.getenv("LIGHTNING_MODEL_INFERENCE_API_INPUT", None)
      output = os.getenv("LIGHTNING_MODEL_INFERENCE_API_OUTPUT", None)
      return cls(input=input, output=output)
  
imports: import abc
  import inspect
  import os
  import pydoc
  import subprocess
  import sys
  from typing import Any, Callable, Optional
  import fastapi
  import uvicorn
  from fastapi import FastAPI
  from fastapi.responses import JSONResponse
  from lightning.app.components.serve.types import _DESERIALIZER, _SERIALIZER
  from lightning.app.core.work import LightningWork
  from lightning.app.utilities.app_helpers import Logger
label_desc: Use image node_id 1 for calling a global function with example usage: _maybe_create_instance() and returns: cls, None